Higher-order resting state network association with the useful field of view task in older adults

Abstract

Speed-of-processing abilities decline with age yet are important in performing instrumental activities of daily living. The useful field of view, or Double Decision task, assesses speed-of-processing and divided attention. Performance on this task is related to attention, executive functioning, and visual processing abilities in older adults, and poorer performance predicts more motor vehicle accidents in the elderly. Cognitive training in this task reduces risk of dementia. Structural and functional neural correlates of this task suggest that higher-order resting state networks may be associated with performance on the Double Decision task, although this has never been explored. This study aimed to assess the association of within-network connectivity of the default mode network, dorsal attention network, frontoparietal control network, and cingulo-opercular network with Double Decision task performance, and subcomponents of this task in a sample of 267 healthy older adults. Multiple linear regressions showed that connectivity of the cingulo-opercular network is associated with visual speed-of-processing and divided attention subcomponents of the Double Decision task. Cingulo-opercular network and frontoparietal control network connectivity is associated with Double Decision task performance. Stronger connectivity is related to better performance in all cases. These findings confirm the unique role of the cingulo-opercular network in visual attention and sustained divided attention. Frontoparietal control network connectivity, in addition to cingulo-opercular network connectivity, is related to Double Decision task performance, a task implicated in reduced dementia risk. Future research should explore the role these higher-order networks play in reduced dementia risk after cognitive intervention using the Double Decision task.

Keywords: Attention; Functional magnetic resonance imaging; Healthy aging; Resting state networks; Speed-of-processing.

Fig. 1

POSIT Science Brain HQ assessment still photos. Reproduced and adapted from POSIT Brain HQ, used with permission. Panel A = Hawk Eye, panel B = Divided Attention, panel C = Double Decision

Fig. 2

Visualization of ROI-ROI connections. A Anterior, B superior, C right hemisphere. Color depicts distinct networks [25]

Fig. 3

Regressions of cingulo-opercular (CON) and frontoparietal control (FPCN) network connectivity and POSIT measures with 95% confidence intervals (n = 267 for all panels). Colors match network color scheme in Fig. 2. A Hawk Eye and CON; B Divided Attention and CON; C Double Decision and CON; D Double Decision and FPCN; r² reflects variance explained from the partial correlation between resting-state network connectivity and POSIT assessment performance; β = standardized beta; x-axis = residuals of resting state network connectivity controlling for scanner, sex, education, and age; y-axis = log transformed POSIT performance